Solutions of the exercises of Andrew Ng's Machine Learning course available on Coursera (in Python).

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

This repository contains some notes on Machine Learning and Deep Learning topics. Mainly based on Andrew Ng's courses on Coursera. Written in Latex with Overleaf editor.

Welcome to my collection of notes for the Stanford Machine Learning course, led by Professor Andrew Ng. These notes are a compilation of insights, key takeaways, and important concepts I gathered while studying the course material.

This repository contains programming assignments for the Deep Learning Specialization by deeplearning.AI. It includes Jupyter Notebooks for exercises in neural networks, hyperparameter tuning, convolutional networks, and sequence models.

This repository is a curated collection of beginner to advanced level tutorials covering a wide range of machine learning concepts and techniques.

This repository contains my lab works and certificates for the Machine Learning Specialization courses by Andrew Ng.

Contains Optional Labs and Solutions of Programming Assignment for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2023) by Prof. Andrew NG

This is my SEM_5 machine learning repo full of things that i learned through out my IML (Introduction to ML) subject.

This repository house all my submission, notes, and related code for this specialization having five courses.

This includes the slides related to coursera Machine Learning Specialization by Andrew Ng.

Here I will put all of my mental notes in structured format while learning the course related to DeepLearning or just LLMs in general!

I have been working on a logistic regression project from scratch, without relying on external libraries like scikit-learn, to predict whether a patient has breast cancer or not. Typically, breast cancer is classified into two categories: malignant (positive) and benign (negative).

Contains all course modules, exercises and notes of ML Specialization by Andrew Ng, Stanford Un. and DeepLearning.ai in Coursera

Taught by AI genius Andrew NG, this course entails the cutting edge topics such as, How generative AI works including what it can and can't do, Common uses cases such as Reading, Writing, and Chatting, Life Cycle of GenAI projects, Advanced Technology options such as RAG, Fine tunning, and Pre-Training, Implications of GenAI on business & Society.

This repo has been created to share the solutions of all the quizzes and assignments of all three courses of this specialization.

Tools for machine learning from two courses machine learning specialization and deep learning specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network…

Programming Assignments and Lectures of Machine Learning by Andrew Ng of Stanford on Coursera

Course content related to Machine Learning Specialization by Andrew Ng